Segmentation and quantification of blood vessels in 3D images using a right generalized cylinder state model

Leonardo Flórez-Valencia, Jacques Azencot, Fabrice Vincent, Maciej Orkiszl, Isabelle E. Magnin

Producción: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

11 Citas (Scopus)

Resumen

We present a vascular segmentation and quantification method based on the right generalized cylinder state model (RGC-sm). The RGC-sm model includes a curvilinear axis associated to a stack of contours. The axis is described by a state vector (local curvature, torsion and rotation). The contours are described by a Fourier series decomposition. The challenge is to automatically adjust this model to 3D vascular data (segmentation). By fitting the synthetic model to the actual medical data, it is possible to get the state model parameters and quantification measures. We present quantitative results on a set of calibrated phantoms and qualitative results on clinical datasets (carotid 3D-CTA and aortic 3D-MRA).

Idioma originalInglés
Título de la publicación alojada2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Páginas2441-2444
Número de páginas4
DOI
EstadoPublicada - 2006
Publicado de forma externa
Evento2006 IEEE International Conference on Image Processing, ICIP 2006 - Atlanta, GA, Estados Unidos
Duración: 08 oct. 200611 oct. 2006

Serie de la publicación

NombreProceedings - International Conference on Image Processing, ICIP
ISSN (versión impresa)1522-4880

Conferencia

Conferencia2006 IEEE International Conference on Image Processing, ICIP 2006
País/TerritorioEstados Unidos
CiudadAtlanta, GA
Período08/10/0611/10/06

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